1. Technological Field
The present disclosure relates to parallel networks (such as e.g., development of computerized neural networks).
2. Background
Parallel networks may be utilized in a variety of applications such as, for example, image processing, object recognition, classification, robotics, and/or other. Such networks may comprise multiple nodes (e.g., units, neurons) interconnected with one another via, e.g., synapses (doublets, connections).
Network units and/or connections may be characterized by unit/connection memory. Individual units/connections may be characterized by their respective individual (at times quite different) pieces of code (rules) that may operate on different memory elements inside neural network. In order to achieve consistent and reproducible results, individual rules should be executed in the right order. It may be desirable to operate multiple nodes of the network in parallel (contemporaneous) with one another. Multiple threads are often used in order to execute network code portions in parallel on a single and/or multiple core processing platform. In order to ensure the correct order of execution in a multithreaded network realization thread synchronization may be employed. However, thread synchronization may reduce thread execution speed particularly when multiple thread synchronization points exist.
By way of illustration, a parallel network may comprise multiple Integrate-and-Fire (IF) units/neurons characterized by update rule configured to operate on unit ‘voltage’. The IF neurons may be interconnected by simple connections that may be configured to update unit voltage and connection weight w. The network may further comprise multiple neurons operable in accordance with spike-response process (SRP). The SRP neurons may be interconnected by complex synapses that may be configured to update connection weight and ‘trace’ variables. The trace variables may characterize various plasticity rules and mechanisms guiding behavior of both simple and complex synapse systems. IF and SRP neuron populations may be randomly connected with randomly distributed synapses of simple and complex type. Some IF neurons may be connected to simple and/or complex synapses at the same time). Pre-synaptic event rules (synapse rules configured to be executed after the spike/event generated by the pre-synaptic unit) have to be executed before unit update rules.